Build the Future of AI Automation

Join a fast-growing AI product company building enterprise-grade voice, chat, and automation platforms

Open Positions

You will develop scalable backend services, integrate LLMs/APIs, and optimize AI model performance in real-world environments.
Strong expertise in Python, FastAPI/Flask, REST APIs, and cloud platforms (AWS/Azure/GCP) is required.
Experience with LLM frameworks, prompt engineering, vector databases, and data pipelines is preferred.
You should be comfortable owning features end-to-end in a fast-paced, product-driven AI environment.

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You will assist in building backend APIs, integrating AI models, and maintaining scalable Python services.
Basic knowledge of Python, REST APIs, databases, and cloud fundamentals is required.
Exposure to LLMs, prompt engineering, or AI frameworks is a plus but not mandatory.
You should be eager to learn, write clean code, and grow in a fast-paced AI product environment.

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We are seeking a RAG Expert to design and optimize retrieval-augmented generation systems for enterprise AI applications.
You will build and manage vector databases, embedding pipelines, chunking strategies, and semantic search architectures.
Strong experience with LLM integration, prompt engineering, LangChain/LlamaIndex, and evaluation frameworks is required.
You should be proficient in Python, APIs, and scalable cloud deployment environments.
The role requires improving retrieval accuracy, reducing hallucinations, and delivering production-ready AI systems.

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We are seeking a Voice AI Expert to build, fine-tune, and optimize speech-based AI systems for enterprise automation.
You will work on ASR, TTS, voice models, intent detection, and conversation flow optimization in production environments.
Strong experience with model fine-tuning, prompt tuning, latency optimization, and real-time voice processing is required.
Proficiency in Python, speech frameworks, LLM integration, and cloud deployment (AWS/Azure/GCP) is expected.
The role focuses on improving voice accuracy, naturalness, response speed, and overall call automation performance.

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